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\begin{Eabstract}{Natural language processing}{named entities}{Conditional random field}{elementary mathematic}{}
Natural language is the carrier of human civilization. With the development of computer science, the research of artificial intelligence technology focuses on the possibility of communication between computer and human. The recognition of named entities has become one of the most important subjects in the field of Natural Language Processing. So far, the research has become more and more valued. On the basis of named entities, the concept of knowledge reasoning has been put forward, and knowledge reasoning is the most important and the core problem of machine learning and deep-learning. 
Based on CRF (Conditional Random Fields) model identification, we reached the goal of tagging mathematical named entities in elementary mathematics texts. Learning from previous experiences, we selected the feature of tagging which is suitable for labeling mathematical entities as the characteristic set for system training, and chose a proper feature template. The effectiveness of the features used in the CRF model has been verified and analyzed. 
In this paper, by combining theory and practice, we study the method of how to select the key information from the probability and statistic questions of elementary mathematics . So we research from the fellow aspects.

1. Algorithms available for named entity tagging

For Chinese named entity recognition, there have been many successful practices at home and abroad, applications of which are usually based on probabilistic graph models. In this paper, some probabilistic models had been applied to Chinese named entity recognition are researched and compared.

2.The named entity tagging in the case of elementary probability and statistic questions.

First the language characteristics of elementary mathematical probability and statistic questions are analyzed. Then according to the actual problem-solving process, a set of named entity labels with practical significance in elementary mathematical probability and statistical questions is determined.

3.Algorithm available for named entity tagging in elementary mathematics based on CRF.

Characteristic function must be provided while using CRF algorithm. In this paper  we analyzes the characteristics function, and design the combination characteristics and atom characteristics as well, inspiring by the from and the part-of-speech of words. 
Finally, a named entity recognition system for probabilistic and statistic problems of elementary mathematics based on CRF is constructed.
\end{Eabstract}
